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Contoh Desain Slide Presentasi Ilmiah Kreatif dan Menarik #4

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Ketika saya mengampu mata kuliah permodelan sistem, di mana mata kuliah ini merupakan mata kuliah untuk mahasiswa tingkat 3, saya menugaskan mahasiswa untuk melakukan sebuah penelitian sederhana dengan menerapkan prinsip - prinsip ilmiah ke lapangan langsung. Saya juga menantang mereka untuk dapat mempresentasikan hasil penelitian mereka dengan tampilan slide yang tidak biasa dan menjemukan. Hingga akhirnya, inilah beberapa di antaranya. Bagaimana menurut Anda?

Publié dans : Formation
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Contoh Desain Slide Presentasi Ilmiah Kreatif dan Menarik #4

  1. 1. PARKING SYSTEM MODELLING of Mall Ambassador Group 7 Anindya Alfi Septyanti (1306448110) Anggi Hazella (1306370051) Felisa Fitriani (1306369945) Nadila Aristiaputri (1306393023) Natasya Sheba S (1306370146) Timotius Alfin (1306409633) Dosen Pembimbing : Arry Rahmawan, ST, MT
  2. 2. 2 Mall Ambassador Capacity 360 parking spots. Parking Lot Has 3 basement levels of parking lot. Location Jl. Prof.Dr.Satrio No. 14, Kuningan, Jakarta Selatan, Banten 15810, Indonesia Working Hours 10.00 – 22.00
  3. 3. Mall Ambassador is one of the most favorite place for people in the terms of buying electronics and shopping clothes. Among other malls and shopping centers that also sell variety of electronics, Mall Ambassador gives more affordable prices than other places. Branded cheap clothes can also be found here. 3
  4. 4. 4 Problem Formulation Model Conceptualization Formal System Modelling Methods Data Collection and Analysis Model Construction Validation and Verification 1 2 3 4 5 Project Report and Presentation 6
  5. 5. Problem Formulation
  6. 6. 6 With such high visitors coming to Mall Ambassador and many of them drive cars, this Mall only provides small spaces for parking – only 360 parking spots available – causing a queue when entering the parking spot and difficulties in finding the parking spot, especially on peak time. Problem Statement
  7. 7. 7 Make the model based on the data we obtained from observation. Based on the model we can conclude whether the parking system of Mall Ambassador is already optimum and met the criteria that had given previously. Objectives
  8. 8. Model Conceptualization
  9. 9. 9
  10. 10. Data Collection and Analysis
  11. 11. 11 Determining data requirement Source of data Analyze the data using software Step of Data Collection
  12. 12. 12 Arrival time Quantity of parking areaService time Arrival rate Pattern of parking area Distribution Number of servers Duration time at the Mall Data Requirement Searching time Working hour Peak hour What do we need to do simulation?
  13. 13. 13 System Documentation We made a documentation of layout and quantity parking area Personal Observation We did personal observation such as direct observation and made a questionnaire Personal Interviews We interviewed Mr. Zaeni as Head of Parking Area at Ambassador Mall Resource of Data Where are the data come from?
  14. 14. 14 Mall Ambassador Jakarta Place 26 September 2015 Date 10.00 am – 10.00 pm Time Observation
  15. 15. Result of Data Observation 15
  16. 16. 16 Data Processing in Observation We observed from 10.00 am until 22.00 (12 hours), then we processed data to determine peak hours in Ambassador Mall. The result is from 11.00-17.00 is peak hours in Ambassador Mall 131 228 255 195 158 187 144 127 83 79 66 35 0 50 100 150 200 250 300 Number  of  Car Arrival  Rate
  17. 17. Data Processing in Observation 228 255 195 158 187 144 0 50 100 150 200 250 300 Arrival  Rate  in  Peak  Hour   avg  arrival   rate 7.20 5.40 5.51 6.24 5.44 5.84 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 Service  Time  in  Peak  Hour avg  service   time   15.79 14.07 18.44 22.76 19.04 24.95 0.00 5.00 10.00 15.00 20.00 25.00 30.00 Inter  Arrival  Time  in  Peak  Hour avg  inter   arrival  time   17
  18. 18. 18 Spreadsheet
  19. 19. 19 Data Analysis in Observation Arrival Rate Service Time
  20. 20. 20 Data Analysis in Observation Searching Time Inter Arrival Time
  21. 21. 21 Questionnaire The questionnaire consists of: 01 How often do they go to Mall Ambassador 02 Time interval in entering the Mall Ambassador 03Duration of parking time in Mall Ambassador 04 The length of waiting time in queue
  22. 22. 22 Result of Questionnaire 20 44 21 8 0 5 10 15 20 25 30 35 40 45 50 10.00-­‐12.00 12.00-­‐15.00 15.00-­‐18.00 18.00-­‐21.00 Arrival  TimeQuestionnaire Arrival  Time 10.00-­‐12.00 20 12.00-­‐15.00 44 15.00-­‐18.00 21 18.00-­‐21.00 8 Time  Duration 1-­‐2  jam 27 2-­‐3  jam 50 >3  jam 16 27 50 16 0 10 20 30 40 50 60 1-­‐2  jam 2-­‐3  jam >3  jam Time  Duration
  23. 23. 23 Data Analysis in Questionnaire This distribution shows the distribution of data from questionnaire is normal distribution.
  24. 24. 1 2 3 4 5 67 89
  25. 25. 25 Attachments Form Online Questionnaire
  26. 26. Model Construction
  27. 27. 27 Model Construction Put a layout as background for the model Build location and Location Logic for the model Build Entities and Entities Logic for the model Build Process and Process Logic for the model Build Arrivals and Arrival Logic for the model 1 2 3 4 5 Run the model 6 Entrance Queue Locket Parking Area Exit
  28. 28. Put a layout as background for the model 28
  29. 29. Build Location and Location Logic for the model 29
  30. 30. 30 Build Location and Location Logic for the model
  31. 31. Build Entities and Entities Logic for the model 31
  32. 32. Build Process and Process Logic for the model 32
  33. 33. Build Arrivals and Arrivals Logic for the model 33
  34. 34. Run the model 34 Click to watch the video of model simulation
  35. 35. Validation and Verification
  36. 36. 36 01 Watching the animation 02 Comparing with other models 03Conducting degeneracy and extreme condition test Validation We use these following techniques for validating the model: 04 Performing sensitivity analysis 05Running trace
  37. 37. 37 Watching the Animation After the model was done, we have to run the model to see whether the model is correct or not.
  38. 38. Comparing with Other Models We have to make sure the model is correct by comparing with the excel data. After we run the model, we can see the statistic, if the number is the same with the excel calculating, then our model is finally correct 38
  39. 39. 39
  40. 40. 40 Conducting Degeneracy and Extreme Condition Test In conducting degeneracy and extreme condition test we can change the arrival rate. Assume that we change the arrival rate to 0 (zero) following with the accuracy, then the result should be: No car arrive in the entry queue. If it is happened, then our model is finally correct
  41. 41. In performing sensitivity analysis, we can try to change the service time, if we change into the smaller number of service time there will be no queue, if we change into bigger number there will be queue. After we try, our model adjust with the changing of numbers, it means the model is correct Performing Sensitivity Analysis 41
  42. 42. 42 Running Trace Running trace will show all of the event on the discrete model. There is no error on our model, based on the trace results
  43. 43. 43 01 Reviewing model code 02 Checking for reasonable input and output 03Watching the animation Verification In order to verified the model, we use some techniques: 04 Using trace and debugging facilities
  44. 44. Reviewing Model Code 44
  45. 45. Checking for Reasonable Input and Output 45 The number of entry car is same as the number of exit car and the number of car at the current location, so input and output are reasonable.
  46. 46. Watching the Animation We can know that the model is correct if the model is running until it’s done correctly and without bug. 46
  47. 47. 47 Using Trace and Debugging Facilities We use trace and debugging facilities to make sure we build the model correctly implemented with good input and structure. There is no error on our model, based on the trace results. There is no debugging in our model.
  48. 48. Results and Recommendations
  49. 49. 49 01 The peak time is at 11.00-17.00 02 -Arrival Rate at peak Time: P(195;41.8) sec -Service Time at peak Time: L(5.94;0.69) sec 03Average waiting time in queue: 0.15 sec Results Our Result is: 04 Average cars in queue: 0.01 05 The data from spreadsheet is same with the data from promodel
  50. 50. 50 01 The capacity should be increased by 25 parking slot to meet the requirement. 02 The number of ticket locket is enough to meet the requirement. Recommendation Our Recommendation is:
  51. 51. THANK YOU!

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